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Nuclear DNA-Gated Electrochemiluminescence Microscopy with Deep Learning for Single-Cell Apoptosis Profiling
Shi-Yi Zhou1, Yihan Qian1, Zhichen Zhang2
1School of Chemistry and Chemical Engineering, Yangzhou University, 225002 Yangzhou, P. R. China.
Abstract:
Accurately assessing how individual cells respond to anticancer agents remains challenging because most assays provide bulk or binary readouts and cannot translate single-cell imaging into scalable, mechanism-relevant quantification. Here, we develop a nuclear DNA-gated electrochemiluminescence (ECL) microscopy assay in which genomic DNA acts as an intrinsic coreactant for Ru(bpy)32+, converting apoptosis-associated chromatin condensation and fragmentation into spatially resolved decreases in nuclear ECL intensity. The resulting signal provides a dose- and time-dependent measure of the apoptotic progression. For drug-treated cells, a deep learning model trained on ECL images enables high-throughput classification of apoptotic and nonapoptotic cells, allowing quantitative apoptosis profiling across large datasets. Using this framework, we compare the apoptotic potency of three natural anticancer compounds and reveal distinct spatial damage signatures for two photosensitizers, reflecting their different ROS-mediated pathways. This integrated approach offers a quantitative and scalable strategy for single-cell apoptosis profiling.
Insights
We developed a novel electrochemiluminescence (ECL) microscopy assay to quantify single-cell apoptosis. This method uses DNA to generate a signal, enabling high-throughput analysis of anticancer drug responses.
Area of Science:
- Cell biology
- Biochemistry
- Microscopy
Background:
- Assessing cellular responses to anticancer drugs is difficult due to limitations in current assays.
- Existing methods often provide bulk or binary readouts, hindering quantitative single-cell analysis.
Purpose of the Study:
- To develop a scalable, quantitative method for single-cell apoptosis profiling.
- To enable mechanism-relevant quantification of cellular responses to anticancer agents.
Main Methods:
- Development of a nuclear DNA-gated electrochemiluminescence (ECL) microscopy assay.
- Utilizing genomic DNA as a coreactant for Ru(bpy)3^2+ to detect chromatin changes.
- Employing a deep learning model for high-throughput classification of apoptotic cells from ECL images.
Main Results:
- The ECL signal quantitatively measures apoptotic progression in a dose- and time-dependent manner.
- The assay successfully profiles apoptosis across large datasets, enabling comparison of drug potencies.
- Distinct spatial damage signatures were identified for photosensitizers, correlating with their ROS-mediated pathways.
Conclusions:
- The developed ECL microscopy assay provides a quantitative and scalable strategy for single-cell apoptosis profiling.
- This approach overcomes limitations of traditional assays, offering mechanism-relevant insights into anticancer agent efficacy.
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